On solving linguistic bi-level programming problem using dynamic programming

被引:0
作者
Singh V.P. [1 ]
机构
[1] Visvesvaraya National Institute of Technology, Nagpur
关键词
Bi-Level programming; Dynamic programming; Fuzzy inference schemes; Fuzzy rule-base; Linguistic variable;
D O I
10.4018/IJFSA.2021010103
中图分类号
学科分类号
摘要
In this work, a linguistic bi-level programming problem has been developed where the functional relationship linking decision variables and the objective functions of the leader and the follower are not utterly well known to us. Because of the uncertainty in practical life decision-making situation most of the time, it is inconvenient to find the veracious relationship between the objective functions of leader, follower, and the decision variables. It is expected that the source of information which gives some command about the objective functions of leader and follower is composed by a block of fuzzy if-then rules. In order to analyze the model, a dynamic programming approach with a suitable fuzzy reasoning scheme is applied to calculate the deterministic functional relationship linking the decision variables and the objective functions of the leader as well as the follower. Thus, a bi-level programming problem is constructed from the actual fuzzy rule-based to the conventional bi-level programming problem. A numerical example has been solved to signify the computational procedure. © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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页码:43 / 63
页数:20
相关论文
共 25 条
[1]  
Agarwal R., Mittal M., Inventory classification using multi-level association rule mining, International Journal of Decision Support System Technology, 11, 2, pp. 1-12, (2019)
[2]  
Bard J., Some properties of the bilevel programming problem, Journal of Optimization Theory and Applications, 68, 2, pp. 371-378, (1991)
[3]  
Bard J. F., Optimality conditions for the bilevel programming problem, Naval Research Logistics Quarterly, 31, 1, pp. 13-26, (1984)
[4]  
Bellman R., Dynamic programming and lagrange multipliers, Proceedings of the National Academy of Sciences of the United States of America, 42, 10, pp. 767-769, (1956)
[5]  
Bialas W. F., Karwan M. H., Two-level linear programming, Management Science, 30, 8, pp. 1004-1020, (1984)
[6]  
Candler W., Townsley R., A linear two-level programming problem, Computers & Operations Research, 9, 1, pp. 59-76, (1982)
[7]  
Chakraborty D., Guha D., Multi-objective optimization based on fuzzy if-then rules, Fuzzy Systems (FUZZ), 2013 IEEE International Conference on, pp. 1-7, (2013)
[8]  
Dorfeshan Y., Meysam Mousavi S., A new interval type-2 fuzzy decision method with an extended relative preference relation and entropy to project critical path selection, International Journal of Fuzzy System Applications, 8, 1, pp. 19-47, (2019)
[9]  
Fortuny-Amat J., McCarl B., A representation and economic interpretation of a two-level programming problem, The Journal of the Operational Research Society, 32, 9, pp. 783-792, (1981)
[10]  
Gao Y., Zhang G., Ma J., Lu J., A-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization, Fuzzy Systems. IEEE Transactions on, 18, 1, pp. 1-13, (2010)